USDA turns to satellites and AI to fix crop data after farmer backlash

The U.S. Department of Agriculture (USDA) is launching a pilot project that will lean more on technology to refine its closely watched crop acreage and yield estimates. Agriculture Secretary Brooke Rollins announced the initiative on Tuesday at the Farm Progress Show in Boone, Iowa, following weeks of listening sessions with farmers and agricultural groups.

The pilot will combine improved satellite imagery, geospatial tools, and crop models with traditional farmer polls. The department is also exploring the use of artificial intelligence and machine learning. Rollins said the USDA is working with NASA and other federal agencies to make the reporting more accurate.

The move comes after widespread criticism from farmers, grain traders, and economists over the reliability of USDA data. Deep staff cuts and sharp swings between initial and final estimates for 2025 corn acreage eroded confidence in the numbers. The final estimates, released in January, pushed already low grain prices down more than 5%, squeezing growers already struggling to turn a profit.

Much of the criticism has centered on the National Agricultural Statistics Service, whose reports can move commodity markets and influence federal farm programs. The USDA says the changes are meant to reduce repeated requests for farmer information while improving timeliness and accuracy. It also plans to share more details about its methodologies, survey response rates, and data limitations.

The listening sessions, which began in early August, have revealed deep frustration over data reliability, staffing cuts, and other administration policies affecting the farm economy. Rollins has acknowledged the loss of confidence and said the USDA needs to rebuild trust. The sessions have also become venues for broader grievances, including recent criticism from cattle producers over plans to increase Argentine beef imports.

Rollins plans to hold more listening sessions through the fall as the agency works to restore credibility in its data.